Customizable User Experience System

ABSTRACT

Systems and methods for customizable user experience service include receiving a first user interaction from a user device at a service platform of a service provider. First instructions are retrieved from a predictive management device based on the first user interaction with the service platform. The service platform may provide the first user interaction to the predictive management device from which the predictive management device may determine the first instructions. The service platform generates a first customized user experience based on the first instructions. The first customized user experience is provided to the user device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is related to U.S. Utility Application Ser. No.______(attorney docket number 70481.2112US01 (P3296US1)), filed Jun. 29, 2016,the disclosure of which is incorporated herein by reference in itsentirety.

BACKGROUND Field of the Disclosure

The present disclosure generally relates to electronic prediction andmore particularly to a customizable user experience system that may beused to provide customize electronic content.

Related Art

More and more consumers are conducting transactions over electronicnetworks such as, for example, the Internet. Consumers routinely providevarious information through the electronic networks as part of thetransaction. The transactions, such as a purchase transaction, may takeplace directly between a conventional or on-line merchant or retailerand the consumer, and payment is typically made by entering credit cardor other financial information. Transactions may also take place withthe aid of an on-line or payment service provider such as, for example,PayPal, Inc. of San Jose, Calif. Such payment service providers can maketransactions easier and safer for the parties involved. Purchasing withthe assistance of a payment service provider from the convenience ofvirtually anywhere using a mobile device is one main reason why on-lineand mobile purchases are growing very quickly.

Business entities such as payment service providers, merchants,retailers, and other service providers typically employ a customerservice system where customers may inquire or receive support toquestions or issues that customers may be experiencing in relation to aproduct, a service, or a system of a business entity with which thecustomer is interacting. Customer service systems may include severalsupport platforms including contact centers where a customer mayinteract with a customer service representative, interactive voiceresponse systems (IVR), and/or a customer service website. However,contact centers employing customer service representatives are expensiveto provide, and may become overwhelmed with customer interactions forcertain events or times of day, resulting in a lessened customerexperience in resolving the customer's issue due to wait times. Websitesthat include answers to frequently asked questions (FAQ) and IVR systemsmay be used help reduce the number interactions with a contact center(and, in turn, the cost of providing that contact center) by providingautomated systems that can access solutions to predefined issues orquestions that a customer may have. However, FAQ and IVR systems aregenerally static and do not take into account current conditions of thebusiness entity's systems, are limited to the number of issues orquestions that they may resolve before they become cumbersome to thecustomer, and do not take into account what the customer has alreadydone to resolve a question or issue, which may lead to escalatedcustomer frustration before ultimately calling a contact center.

Thus, there is a need for an improved customer service system.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a schematic view illustrating an embodiment of a serviceprovider system;

FIG. 2 is a schematic view illustrating an embodiment of a predictivemanagement device of the service provider system of FIG. 1;

FIG. 3 is a flow chart illustrating an embodiment of a method ofproviding a cross-platform customer service system;

FIG. 4 is a schematic view illustrating an embodiment of a serviceprovider monitoring device of the service provider system of FIG. 1;

FIG. 5 is a flow chart illustrating an embodiment of a method forproviding data associated with conditions on the service provider systemto a predictive management device;

FIG. 6 is a schematic view illustrating an embodiment of a web server ofthe service provider system of FIG. 1;

FIG. 7 is a flow chart illustrating an embodiment of a method forproviding a customized web page at a user device;

FIG. 8 is a screen shot of an embodiment of a user device displaying acustomized web page at a user device;

FIG. 9 is a screen shot of an embodiment of a user device displayinganother customized web page at a user device;

FIG. 10 is a schematic view illustrating an embodiment of an interactivevoice response (IVR) system of the service provider system of FIG. 1;

FIG. 11 is a flow chart illustrating an embodiment of a method forproviding a customized interactive response to a user device;

FIG. 12 is a schematic view illustrating an embodiment of a contactcenter system of the service provider system of FIG. 1;

FIG. 13 is a flow chart illustrating an embodiment of a method forproviding a customized customer service graphical user interface (GUI)to a customer service terminal;

FIG. 14 is a screen shot of an embodiment of a customer service terminaldisplaying a customized customer service GUI;

FIG. 15 is a screen shot of an embodiment of a customer service terminaldisplaying another customized customer service GUI;

FIG. 16 is a schematic view illustrating an embodiment of a networkedsystem;

FIG. 17 is a perspective view illustrating an embodiment of a userdevice; and

FIG. 18 is a schematic view illustrating an embodiment of a computersystem.

Embodiments of the present disclosure and their advantages are bestunderstood by referring to the detailed description that follows. Itshould be appreciated that like reference numerals are used to identifylike elements illustrated in one or more of the figures, whereinshowings therein are for purposes of illustrating embodiments of thepresent disclosure and not for purposes of limiting the same.

DETAILED DESCRIPTION

The present disclosure provides systems and methods for predictivecross-platform customer service that operates to provide a customizeduser experience to a user (e.g., customer) of a service provider system.The service provider system may include a predictive management devicethat may perform many of the functions of the predictive cross-platformcustomer service system. The predictive management device may haveaccess to a database of historical data such as data related tohistorical conditions of the service provider system, data related tohistorical interactions that user(s) have previously performed with theservice provider system, data related to user accounts, third partydatabases and services, and/or other data stores that allow for thefunctionality described herein. The predictive management device mayalso receive real-time data about present conditions of the serviceprovider system and current interactions of users interacting with theservice provider system. For example, a network management device maymonitor the service provider system and generate information relating tothe conditions of the systems and network of the service provider system(e.g., server speed, latency on the network, application performance,and other relative information about the network and/or components ofthe service provider system that may affect a user's experience with theservice provider system) that is then provided to the predictivemanagement device. In another example, a web server of the serviceprovider system may generate real-time data regarding users of theservice provider's website (e.g., user account information, specific webpages visited by the user, searches performed by the user, and otheruser interaction data related to interactions that a user may perform ata service provider website, along with any metadata associated withthose interactions). In another example, an interactive voice response(IVR) system may generate user interaction data of users interactingwith the IVR system. In yet another example, a contact center server maygenerate interaction data in response to users interacting with customerservice representatives such as, for example, inputs provided bycustomer service representatives while interacting with particularusers.

The predictive management device may include one or more machinelearning algorithms that may generate and provide instructions to acustomer interaction database based on the historical data, real-timedata, and/or any other data generated by the system and received by thepredictive management device. The instructions may be accessible by thevarious customer service platforms of the service provider system (e.g.,a web server, IVR system, a contact center server) and may cause thecustomer service platforms to present information to a user based on thehistorical, real-time, and other data to achieve a customized userexperience. For example, a customized user experience may includeresolving a question or issue of a user without the user establishing acommunication session with a customer service representative. Thepredictive management device may determine, based on the historical,real-time, and other data, conditions on the service provider system,which may include conditions of a user account of the user, thatindicate a threshold probability that the user will establish acommunication session with a customer service representative. Thepredictive management device may then provide instructions for providingthe customized used experience to a user interaction database that isaccessible by the different customer service platforms provided toachieve the customized user experience. The predictive management devicemay receive subsequent real-time data from the various customer serviceplatforms as the customer service platforms execute the instructions toprovide the customized user experience, which may include userinteraction data. The feedback of the user interaction data may be usedby the predictive management device to update the instructions toprovide the customized user experience and/or rules for generating theinstructions to provide the customized user experience. The updatedinstructions may be transmitted directly to the particular customerservice platform and/or may update the instructions stored in the userinteraction databases. The updated instructions may include instructionsfor other customer service platforms besides the customer serviceplatform the user is interacting with. Because the predictive managementdevice is receiving information about a user in real-time from onecustomer service platform, the predictive management device may beconfigured to provide updated instructions to the user interactiondatabase, which may include information regarding the user's lastinteraction with a customer service platform that is now accessible toanother.

Thus, a cross-platform customer service system is achieved, at least inpart, by enabling each of the customer service platforms to access theinstructions to provide the customized user experience and theinformation regarding the user's last interaction with a previouslyaccessed customer service platform. Having information and instructionsavailable across customer service platforms saves time in having torepeatedly gather data from the user and may alleviate frustrations ofthe user in having to provide information multiple times when resolvinga problem. Such customized user experiences may lead to better retentionof customers and more efficient use of customer service system resourcesto reduce costs of the service provider.

Referring now to FIG. 1, an embodiment of a cross-platform customerservice system 100 is illustrated. The cross-platform customer servicesystem 100 includes a service provider system 102 and a user device 104in communication over a network 106. Although only one user device 104is illustrated as being in communication with the service providersystem 102, a plurality of user devices 104 may be in communication withthe service provider system 102 over the network 106 while remainingwithin the scope of the present disclosure. In an embodiment, the userdevice 104 may be provided by a desktop computing system, alaptop/notebook computing system, a tablet computing system, a mobilephone, a landline phone, a wearable computing device and/or other userdevices known in the art. The network 106 may be implemented as a singlenetwork or a combination of multiple networks. For example, in variousembodiments, the network 106 may include the Internet and/or one or moreintranets, landline networks, wireless networks, and/or otherappropriate types of networks. The network 106 may include a datanetwork, a public switched telephone network, and/or a converged networkon which both data communications and voice communications aretransmitted.

The service provider system 102 may include a service provider server107 that may include multiple servers and devices for providing aservice to a user through the user device 104. For example, the serviceprovider server 102 may provide payment services for facilitating onlineand/or mobile payments between a retailer/merchant and a consumer. Inother examples, the service provider system 102 may be an onlineretailer system configured to present and sell products to a consumer, agaming system that provides online gaming to a consumer, a contentprovider system that provides content such as streaming videos to aconsumer, a general consumer support system for an organization, abanking system, and other systems belonging to organizations thatrequire customer support. The service provider server 107 may includemultiple servers and systems for providing the services and/or productsrelated to the service provider's business. The service provider system102 may also include a consumer service system that includes a pluralityof customer service platforms such as a web server 108, an interactivevoice response (IVR) system 110, and a contact center system 112. Inaddition, the service provider system 102 may include one or moredatabases such as a user interaction database 114 and a user accountdatabase 116. Furthermore, the service provider system 102 may include aplurality of networking devices such as a gateway 111, a serviceprovider system (SPS) monitoring device 118, and a predictive managementdevice 120. However, other customer service platforms providing othercustomer service actions and including other devices and subsystems areenvisioned as falling within the scope of the present disclosure. As canbe seen in the illustrated embodiment, the various devices, servers, anddatabases of the service provider system 102 may be in communicationwith each other over a network 122. However, each of the components maycommunicate with each other over the network 106 and/or othercommunication connections that are envisioned as falling within thescope of the present disclosure as well.

The cross-platform customer service system 100 also includes a customerservice terminal 124 from which a customer service representative mayhelp to provide customer service. The customer service terminal mayinclude a telephone for voice communications and/or a computing devicefor receiving information related to a communication session anddisplaying information, videos, etc. to a customer servicerepresentative. As can be seen in the illustrated embodiment, thecustomer service terminal 124 is in direct communication with thecontact center system 112 and is not included in the service providersystem 102. However, it is contemplated that the customer serviceterminal 124 may be in communication with any of the components of theservice provider system 102 through the network 106 and/or the network122, included in the service provider system 102, and provided via otherconfigurations that are envisioned as falling within the scope of thepresent disclosure. Furthermore, the cross-platform customer servicesystem includes a third party database 126 that may be in communicationwith the service provider system 102 through network 106. However, thethird party database may be in communication with the service providersystem 102 through network 122 as well. The third party database 126 mayprovide third party data such as social media data, 3^(rd) party serviceprovider disruptions, credit bureau data, federal compliance andregulatory data, and other third party data for providing customerservice that would be apparent to one of skill in the art in possessionof the present disclosure.

As discussed in further detail below, each of the web server 108, theIVR system 110, the contact center system 112, and the SPS monitoringdevice 118 are configured to collect data, and then provide that data tothe predictive management device 120. Furthermore, the service providerserver 107 may collect data related to the services provided tocustomers and interactions customers have with the service providerserver 107 and provide the data to the predictive management device 120.The data collected from the various sources may be used by thepredictive management device 120 to generate customer service rules andcustomer service instructions that are stored at the user interactiondatabase 114. The web server 108, the IVR system 110, and the contactcenter system 112 may then retrieve and execute the customer serviceinstructions from the user interaction database to provide thecustomized customer experiences to a user of the user device 104 asdescribed below.

Referring now to FIGS. 2, an embodiment of a predictive managementdevice 200 is illustrated. In an embodiment, the predictive managementdevice 200 may be the predictive management device 120 discussed above.In the illustrated embodiment, the predictive management device 200includes a chassis 202 that houses the components of the predictivemanagement device 200, only some of which are illustrated in FIG. 2. Forexample, the chassis 202 may house a processing system (not illustrated)and a non-transitory memory system (not illustrated) that includesinstructions that, when executed by the processing system, cause theprocessing system to provide a predictive user interaction engine 204that is configured to perform the functions of the predictive userinteraction engine 204 and/or the predictive management device 200discussed below. In a specific example, the predictive user interactionengine 204 may be software or instructions stored on a computer-readablemedium that is configured to receive historical, real-time, and otherdata from the service provider system 102 of FIG. 1, generate userinteraction rules based on the historical , real-time, and other data,monitor for conditions on the service provider system 102 based on theuser interaction rules, provide instructions to customer serviceplatforms to provide customized user experiences, provide cross customerservice platform interactions, and provide any of the otherfunctionality that is discussed below.

The chassis 202 may further house a communication engine 206 that iscoupled to the predictive user interaction engine 204 (e.g., via acoupling between the communication system 206 and the processing system)and configured to provide for communication through the network 122 asdetailed below. The communication engine 206 may be software orinstructions stored on a computer-readable medium that allows thepredictive management device 200 to send and receive information overthe network 122. The chassis 202 may also house a user interaction rulesdatabase 208 that is coupled to the predictive user interaction engine204 through the processing system. The user interaction rules database208 may store static and dynamic rules used by the predictive customerinteraction engine 204 to determine conditions on the service providersystem 102 and/or to generate instructions to provide to the customerservice systems of the service provider system 102 based on thedetermined conditions. While the user interaction rules database 206 hasbeen illustrated as housed in the chassis 202 of the predictivemanagement device 200, one of skill in the art will recognize that itmay be connected to the predictive user interaction engine 204 throughthe network 122 without departing from the scope of the presentdisclosure.

Referring now to FIG. 3, a method 300 for providing a customized userexperience across customer service platforms is illustrated. In someembodiments of the method 300, the predictive management device 200 maybe configured to perform or enable the method 300. The method begins atblock 302 where first data is received from a service provider system.In an embodiment, the predictive management device 200 receives datafrom the service provider system 102 of FIG. 1. In some embodiments, thepredictive management device 200 monitors the service provider system102, which may include receiving real-time data in addition tohistorical data from various components of the service provider system102, (e.g., data from the user account database 116, data from the SPSmonitoring device 118, data from the web server 108, data from the IVRsystem 110, and data from the contact center system 112), data from thethird party database 126, and/or data from any other data sources thatone of skill in the art in possession of the present disclosure wouldrecognize would allow the predictive management device 200 to providethe customized user experiences in the cross-platform customer servicesystem as described below.

The method 300 may then proceed to block 304 where the predictivemanagement device determines first user interaction rules based on thefirst data received from the service provider system. In an embodiment,at block 304 the predictive user interaction engine 204 of thepredictive management device 200 may include one or more machinelearning algorithms such as frequent pattern growth heuristics, otherunsupervised learning algorithms, supervised learning algorithms,semi-supervised learning algorithms, reinforcement learning algorithms,deep learning algorithms, and other machine learning algorithms known inthe art. The predictive user interaction engine 204 may be configured togenerate the first user interaction rules based on the real-time dataand historical data received from the service provider system 102 and/orthird party database 126. In an embodiment, the user interaction rulesare rules that the predictive management device 200 follows to determinea condition for which to monitor on the service provider system 102, anddetermine instructions based on conditions that exist in the serviceprovider system 102. For example, the condition may be determined toexist from the real-time data and the historical data used by thepredictive management device 200 to generate the first user interactionrules. In an embodiment, the predictive user interaction engine 204 mayinclude static rules that describe general goals of the service providerand that are updatable by the service provider. For example, a goal ofthe service provider may be to maximize profits, reduce the number ofcommunication sessions between a user and a customer servicerepresentative, retain users as customers, increase consumption by thecertain users, and any other goal, hierarchy of goals, or combination ofgoals that would be apparent to one of skill in the art in possession ofthe present disclosure. The predictive management device may considerthese goals when generating the rules. The predictive management device200 may store the rules in the user interaction rules database 208.

In a specific example, when a goal of the service provider is tominimize costs, the predictive management device may determine thatcustomer service representatives are costly and may establish rules todecrease the number of communication sessions between a user and acustomer service representative. Fewer communication sessions may reducecosts by reducing the number of customer service representatives neededto service the communication sessions. The predictive management device200 may analyze the historical data and the real-time data received fromthe various data sources described above to determine conditions where auser initiated a communication session with a customer servicerepresentative. The predictive management device 200 may then generaterules for monitoring data received at the predictive management device200 to alert the predictive management device 200 when a conditionexists on the service provider system 102 that may result in acommunication session between a user and a customer servicerepresentative.

The method then proceeds to determination block 306 where the predictivemanagement device determines whether a first condition exists on theservice provider system based on the first data received and the firstuser interaction rules. In an embodiment, at block 306 the predictivemanagement device 200 may continue to monitor the service providersystem 102 to determine whether a user interaction rule has beensatisfied based on the real-time and historical data received fromservice provider system 102. Continuing the specific example above, arule identifying possible users that will initiate a communicationsession with a customer service representative may identify users thatdo not receive a refund of a returned item within three days as having ahigher probability of initiating an interaction with a customer servicerepresentative. The predictive management device 200 may then receivedata from user accounts as to whether there are any pending refunds,along with the period of time that has passed since the refund wentpending. When a user account has a pending refund and the period of timeis approaching or at three days, then a condition that is based on thosefirst user interaction rules exists on the service provider system 102.If a first condition does not exist, the method 300 returns to block 302where the predictive management device 200 receives data from theservice provider system 102.

If the first condition does exist at block 306, the method then proceedsto block 308 where the predictive management device determines firstinstructions to provide to the service provider system based on thefirst condition. In an embodiment, in response to determining that acondition exists on the service provider system 102, the predictivemanagement device 200 may determine first instructions to provide to thevarious customer service platforms (e.g., the web server 108, the IVRsystem 110, and the contact center system 112) of the service providersystem 102. In an embodiment, the predictive user interaction engine 204may include machine learning algorithms that may determine what actionor actions to take given the first condition and the first userinteraction rules in order to achieve a particular user response basedon historical data. The predictive user interaction engine 204 maygenerate first instructions based on the actions determined by themachine learning algorithms, and those first instructions may begenerated for one or more customer service platforms (e.g., instructionsfor the web server 108, instructions for the IVR system 110, and/orinstructions for the contact center system 112).

For example, the predictive management device 200, by use of one or moremachine learning algorithms, may determine first conditions in theservice provider system 102 that are similar to second conditions thathave resulted in a user initiating a communication session with acustomer service representative, but which resulted in a customer notinitiating an interaction with a customer service representative. Morespecifically, the predictive management device 200 may determine that afrequently asked question (FAQ) link on the website hosted by the webserver 108 was accessed by a group of users with conditions that are thesame as, or similar to, users that initiated a communication sessionwith a customer service representative. By following the userinteraction rules, the predictive management device 200 may determineinstructions for the web server 108 to more prominently display the FAQlink at a web page of the website when a particular user that satisfiesthe first conditions logs on to their user account through the webserver 108 of the service provider system 102. In another example, thecontact center system 112 may send an email or text message to theparticular user informing them of information that may be found on theFAQ. In another example, the predictive management device 200 may alsodetermine first instructions for the IVR system 110 to provide customersthat call in the information from the FAQ link of the website, orprovide an option to present the information from the FAQ link to a userthat is associated with the first condition when the user initiatescontact with the IVR system 110. The predictive management device 200may also generate first instructions for the contact center system 112such that if the user does establish a communication session with acustomer service representative, the customer service representativewill have all of the user's information, possible reasons for the userinteracting with the customer service representative, and priorinteractions with other customer service platforms (e.g., inquiringabout a refund as in the previous specific example). Because the firstrule of decreasing the number of user communication sessions with acustomer representative was not satisfied, the first instructions mayinclude information for the customer service representative to passalong to the user that may help satisfy the rule in the future such as,for example, pointing to FAQ links on the service provider's websitehosted by web server 108 or other information that may prevent the user,based on positive user experiences, from initiating a communicationsession with a customer service representative.

The method 300 then proceeds to block 310 where the predictivemanagement device provides the first instructions to the serviceprovider system. In an embodiment, predictive management device 200 mayprovide the first instructions over network 122 to the user interactiondatabase 114 to which each customer service platform (e.g., the webserver 108, the IVR system 110, and contact center system 112) hasaccess and from which each customer service system may access, retrieve,receive, and/or read the first instructions. In other embodiments, thepredictive management device 200 may transmit the instructions directlyto a customer service platform. For example, if a user is interactingwith the website of the web server 108, then the predictive managementdevice 200 may transmit the first instructions directly to the webserver 108 over network 122. The web server 108, the IVR system 110, andthe contact center system 112 may execute the first instruction that maybe based on further conditions recognized by each respective customerservice system. For example, the web server 108 may detect a conditiondefined by the first instructions and perform an action based ondetecting the condition defined by the first instructions. The executionof the first instructions for each of the web server 108, the IVR system110, and the contact center system 112 are further described below atmethod 700 of FIG. 7, method 1100 of FIG. 11, and method 1300 of FIG.13, respectively.

The method 300 then proceeds to block 312 where the predictivemanagement device receives second data of a user interaction with atleast one of the customer service platforms. In an embodiment, thepredictive management device 200 may receive second data from thecustomer service platform that is executing the first instruction (e.g.,during the execution of those first instructions, or subsequent to theexecution of those first instructions). The second data may include anyinformation regarding the user's interactions with the customer serviceplatform such as, for example, web pages visited, customer satisfactionsurvey results, responses to questions asked by the customer servicesystem, metadata associated with the user interaction (e.g., type ofdevice, location information, time and duration of interaction, andother relative metadata related to the user interaction), and whetherthe desired user response was achieved.

Continuing the specific example above to illustrate block 312, a usermay access the website hosted by the web server 108. The user may have apending refund and it has been three days since the refund wasinitiated. The web server 108 may query the user interaction database114 to determine whether any first instructions for that particular userexist, and receive the first instructions upon detection of the user. Inanother example, the web server 108 may have retrieved more generalinstructions to monitor certain information about users and performactions based on criteria of user information obtained at the web server108. In either case, if the user has a pending refund, the firstinstructions may cause the web server 108 to provide a customized webpage that may include the status of the refund on the web page the useris currently viewing and/or a link to FAQ about refunds that may providean answer to the user's anticipated question about refunds. The webserver 108 may then transmit second data to the predictive managementdevice 200 relating to how the user interacted with the website afterthe user received the customized web page including the status of therefund and/or the link of the FAQ. For example, if the user left thewebsite after the status of the refund was displayed, or the userselected the FAQ link and then left the website shortly thereafter, thisdata may be reported back to the predictive management device 200 assecond data. Similarly, if the user did select other web page links,performed searches, or performed other actions on the website hosted bythe web server 108, then the web server 108 may transmit related seconddata to the predictive management device 200. Furthermore, thepredictive management device 200 may receive second data from a contactcenter system 112 that indicates that the user initiated a communicationsession with a customer service representative even after viewing thecustomized web page hosted by the web server 108. The second data mayinclude why the user initiated a communication session with the customerservice representative (e.g., because of the refund or other reasons.)The predictive management device 200 may use this second data to furtherevaluate the user interaction rules and/or first instructions providedto the customer service platforms.

The method 300 then proceeds to block 314 where the predictivemanagement device updates the first instructions to second instructionsbased on the second data received as a result of the user interaction.In an embodiment, if the predictive management device 200 receivessecond data that indicates that a desired user response was achieved,the predictive management device 200 may update the first userinteraction rules to generate the second user interaction rules, whichmay be reinforced first user interactions rules as determined by themachine learning algorithms of the predictive user interaction engine204. In an embodiment, where the desired user response was not achieved,the predictive management device 200 may generate second instructionsbased on the first user interaction rule, based on the second userinteraction rule which is an updated version of the first userinteraction rule, or based on a third user interaction rule (which mayhave been hierarchally less significant than the first user interactionrule generated using the first data, and which are hierarchally moresignificant than the second interaction rule generated using the seconddata, or which may provide the next highest significance in comparisonto the first user interaction rules or a completely new user interactionrule that is generated based on the second data.)

For example, the refund status of the user's refund may have beenprovided on a customized web page of the website hosted by the webserver 108, and the user may have selected different links on the webpage not related to the refund. Web server 108 may provide the userinteraction data with the customized web page to the predictivemanagement device 200. The predictive management device 200 maydetermine, based on the user interaction data, that the user also has apending exchange of goods and may also determine second instructions toprovide to the customer service platforms based on the exchange ofgoods, which may include second instructions provided directly to theweb server 108 to update the customized web page to provide informationregarding the user's exchange of goods.

Referring now to FIG. 4, an embodiment of a service provider system(SPS) monitoring device 400 is illustrated. In an embodiment, the SPSmonitoring device 400 may be the SPS monitoring device 118 discussedabove in FIG. 1. In the illustrated embodiment, the SPS monitoringdevice 400 includes a chassis 402 that houses the components of the SPSmonitoring device 400, only some of which are illustrated in FIG. 4. Forexample, the chassis 402 may house a processing system (not illustrated)and a non-transitory memory system (not illustrated) that includesinstructions that, when executed by the processing system, cause theprocessing system to provide a SPS monitoring engine 404 that isconfigured to perform the functions of the SPS monitoring engine 404and/or the SPS monitoring device 400 discussed below. In a specificexample, the SPS monitoring engine 404 may be software or instructionsstored on a computer-readable medium that is configured to perform tests(e.g., regression tests) and gather data (e.g., server status,application status, network latency, network load, and application layerfunctionality data) about the components and functionality of thecomponents of the service provider system 102 (e.g., software, hardware,and network functionality) and provide any of the other functionalitythat is discussed below that one of skill in the art in possession ofthe present disclosure will recognize as computer functionality that maybe enabled by the SPS monitoring engine 404 as well. The chassis 402 mayfurther house a communication engine 406 that is coupled to the SPSmonitoring engine 404 (e.g., via a coupling between the communicationsystem 406 and the processing system) and configured to provide forcommunication through the network 122 as detailed below. Thecommunication engine 406 may be software or instructions stored on acomputer-readable medium that allows the SPS management device 400 tosend and receive information over the network 122. The chassis 402 mayalso house an SPS monitoring rules database 408 that is coupled to theSPS monitoring engine 404 through the processing system. The SPSmonitoring rules database 408 may store rules used by the SPS monitoringengine 404 to determine conditions of the components of the serviceprovider system 102. While the SPS monitoring rules database 408 hasbeen illustrated as housed in the chassis 402 of the SPS managementdevice 400, one of skill in the art will recognize that it may beconnected to the SPS monitoring engine 404 through the network 122without departing from the scope of the present disclosure.

Referring now to FIG. 5, a method 500 for providing service providersystem data to a predictive management device is illustrated. In someembodiments of the method 500, the SPS monitoring device 400 may beconfigured to perform or enable the method 500. The method 500illustrates an embodiment of the first data received by the predictivemanagement engine as described above at block 302 of the method 300illustrated in FIG. 3. As described above, with respect to block 302,the predictive management device 200 may receive first data that mayinclude data from the SPS monitoring device 400. The data from the SPSmonitoring device 400 may be backend data such as performance datarelating to the components of the service provider system (e.g., thephysical operations of the web servers, networking devices, IVR system,databases, applications, third party API services, and other serviceprovider system infrastructure).

The method 500 begins at block 502 where a SPS monitoring devicemonitors the components of the service provider system 102. In anembodiment, the SPS monitoring device may receive and/or gather data ofthe various components of the service provider system 102. The data maybe performance data such as component errors, component loads, networklatency, response times, transaction rate, network utilization,processing utilization, database utilization, and any other performancedata of components of a service provider system 102 including hardwareand software that would be apparent to one of skill in the art inpossession of the present disclosure.

In an embodiment, the SPS monitoring device 400 may transmit anyperformance data gathered to the predictive management device 200, andthe predictive management device 200 may determine whether anyconditions exist based on the performance data, and/or make anycorrelations via the machine learning algorithms based on theperformance data provided by the SPS monitoring device. In otherembodiments, the method 500 then proceeds to block 504 where the SPSmonitoring device determines whether a condition exists based on theperformance data received from the service provider system 102 and basedon SPS monitoring rules. The method 500 then proceeds to decision block506 where the SPS monitoring device 400 continues to monitor the serviceprovider system at block 502 if the condition does not exists, or themethod 500 proceeds to block 508 and provides first data such as anotification of the condition to the predictive management device 200.

In an embodiment of block 504, the SPS monitoring engine 404 of the SPSmonitoring device 400 may determine, based on the data gathered at block502 of method 500 and SPS monitoring rules stored in the SPS monitoringrules database 408, whether a condition exists relating to theperformance of the components of the service provider system 102. In anembodiment, the SPS monitoring rules may be thresholds on variousperformance metrics. For example, an SPS monitoring rule may be if theload on a web server gets above a certain threshold, a notification willbe transmitted to the predictive management device indicating that athreshold has been met as at block 508. The SPS monitoring rules storedin the SPS monitoring rules database 408 may be implemented by a systemadministrator and may be static in that they monitor for staticthresholds. However, in other embodiments, the SPS monitoring rules maybe updated by the predictive management device 200 such that the SPSmonitoring rule are dynamic.

For example, the SPS monitoring rules may provide data to the predictivemanagement device 200 if, for example, the response time for a websiteof a webserver is greater than a first time. The first time may be athreshold where users of the service provider system 102 may begininitiating a communication session with a customer servicerepresentative which, continuing with the examples above, would violateone or more user interaction rules of the predictive management device200 based on goals of customer satisfaction and minimizing costs of theservice provider system 102. Transmitting the notification to thepredictive management device 200 that the load has reached a thresholdmay cause the predictive management device 200 to generate instructionsto inform the various customer service platforms that a web server isexperiencing a high load at this time in an attempt to prevent the userfrom initiating a communication session with a customer servicerepresentative. For example, the predictive management device 200 maygenerate an instruction for the IVR system 110 to generate aninteractive response for a user interacting with the IVR system 110 ifthe user is experience a slower than normal experience with the serviceprovider's website, and provide a reason and/or solution to resolve theissue of the slower website if the user responds affirmatively to thegenerated interactive response.

Furthermore, the predictive management device 200 may begin to receivedata from the contact center system 112 that users are initiatingcommunication sessions with customer service representatives about thespeed of the website before the predictive management device 200receives a notification from the SPS monitoring device 400, which may bean indication that user expectation about speed has changed. Thereforethe predictive management device 200 may update the SPS monitoring rulesin the SPS monitoring rules database 408 to reflect the change in userexpectations.

Referring now to FIG. 6, an embodiment of a web server 600 isillustrated. In an embodiment, the web server 600 may be the web server108 discussed above in FIG. 1. In the illustrated embodiment, the webserver 600 includes a chassis 602 that houses the components of the webserver 600, only some of which are illustrated in FIG. 6. For example,the chassis 602 may house a processing system (not illustrated) and anon-transitory memory system (not illustrated) that includesinstructions that, when executed by the processing system, cause theprocessing system to provide a web server engine 604 that is configuredto perform the functions of the web server engine 604 and/or the webserver 600 discussed below. In a specific example, the web server engine604 may be software or instructions stored on a computer-readable mediumthat is configured to gather frontend data about users interacting withthe web server 600 (e.g., web pages visited of the website hosted by theweb server 600, data inputted by the user, data regarding the usersbrowser, location of the user, type of user device 104 the user is usingto access the web server, click-through rates of links on the website,amount of time a user spends on a web page, survey feedback from theuser, and other user related data that a web server may gather known inthe art). In a specific example, the web server engine 604 may besoftware or instructions stored on a computer-readable medium that isconfigured to generate and provide a customized web page to be displayedon a user device (e.g., user device 104) based on instructions generatedby a predictive management device, and provide any of the otherfunctionality that is discussed below.

The chassis 602 may further house a communication engine 606 that iscoupled to the web server engine 604 (e.g., via a coupling between thecommunication system 606 and the processing system) and configured toprovide for communication through the network 122 and/or the network 106as detailed below. The communication engine 606 may be software orinstructions stored on a computer-readable medium that allows the webserver 600 to send and receive information over the network 122 and/orthe network 106. The chassis 602 may also house a web page database 608that is coupled to the web server engine 604 through the processingsystem. The web page database 608 may store web pages and or objects ofweb pages that may be used to generate customized web pages based oninstructions generated by the predictive management device 200. Whilethe web page database 608 has been illustrated as housed in the chassis602 of the web server 600, one of skill in the art will recognize thatit may be connected to the web server engine 604 through the network 122and/or network 106 without departing from the scope of the presentdisclosure.

Referring now to FIG. 7, a method 700 for generating a customized userexperience via a web server is illustrated. The method 700 begins atblock 702 where a web server determines user interaction with a websitefrom a user device. In an embodiment, the web server 600 may detect userinteraction with a web page of a website via requests received from theuser device 104, and gather any information about the user interactioninclude user information, location information, user device 104 type,current web page of the website, whether the website was accessed by amobile application or web browser, time of interaction, Internetprotocol address or any other device identifier, authenticated sessioninformation, and any other information that may be captured from a userinteraction with a website and that would be apparent to one of skill inthe art in possession of the present disclosure. In an embodiment, theweb server may transmit the information about the user interaction tothe predictive management device 200 as the first data described above.

The method 700 proceeds to block 704 where the web server receivesinstructions from a predictive management device based on theinteraction. In an embodiment, the web server 600 directly receivesinstructions from the predictive management device 200. Alternatively oradditionally, the web server 600 receives instructions from the userinteraction database 114. In an embodiment, the instructions may beglobal instructions that address general conditions on service providersystem 102 that may affect a large group of users of the serviceprovider system 102. For example, if there is a server failure on theservice provider system 102 that provides services to the users, theinstructions may be configured to address the server failure. In anembodiment, the instructions may be midlevel instructions that addressconditions for a particular population of users. For example, there maybe a condition in a specific city or region such that users in thatregion more likely to initiate a communication session with a customerservice representative. Although the example illustrates location as acondition to provide the instructions at midlevel instructions, otherconditions may be relevant in determining instructions such as age ofthe user, web browser type, time of day, events being provided by theservice provider system 102 (e.g., a content provider is providing apay-per-view event), and other conditions apparent to one skilled in theart.

In an embodiment, the instructions may be individual instructions thataddress a condition for a particular user, user account, and/or userdevice that is accessing the web server 600. In this embodiment, thewebserver may gather an identifier of the user/user device such as useraccount information due to a login, and/or a device identifier of theuser device 104. For example, the instructions may be based on recentactivity of the user. The web server 600 may determine that a particularuser logged into their account with the service provider system 102, andthe web server 600 may transmit the user account information to thepredictive management device 200. The predictive management device 200may determine instructions based on the condition that is the useraccount information. The user account information may include recentactivity of the user associated with the user account such that therecent activity as first data may be used to determine a conditionexists along with an instruction based on the condition as in blocks 306and 308 of method 300 described above. For example, the recent activityof a user account that has interacted with the web site of the webserver 600 and accessed the user's account may indicate that the userpurchased two of the same items but in different sizes, and the itemshave been shipped and received by the user. The predictive managementdevice 200 may determine that under these conditions the user is likelylooking for return information for one of the items, and may generateinstructions that address returning items and obtaining a refund. Thepredictive management device 200 may also determine that the user may belooking for exchange information to exchange one or more of the itemsfor a different item. However, this scenario may be less likely thanreturning an item, which the instructions may take into account ascausing the web server 600 to present the less likely scenario second tothe more likely scenario, or in a less prominent area of the web page.

The method 700 proceeds to block 706 where the web server generates acustomized website based on the instructions. In an embodiment, the webserver 600 may generate one or more customized web pages based on theinstructions received from the user interaction database 114 and/or thepredictive management engine 200. The method 700 then proceeds tooperation 708 where the customized website is provided for display onthe user device. In an embodiment, the web server 600 may provide thecustomized web pages of the customized web site to the user device 104,and the user device 104 may display the customized web page on a displayof the user device 104.

FIG. 8 illustrates a screen shot of a specific example of how web server600 may generate a customized web page 802 according to block 706 andblock 708 of method 700 discussed above. The web server 600 maydetermine a user interaction with the website hosted on the web server600 through a web browser 800 on the user device 104. The interactionmay be a frequently asked questions (FAQ) web page as illustrated by webpage 802 of FIG. 8. The first instruction based on the informationprovided about the interaction by the user may be to display links togeneral FAQ (e.g., top FAQ that are common for a global audience). Theweb server 600 may generate the web page 802 and provide the web page802 to the user device 104 to be displayed via the web browser 800 onthe display of the user device 104. For example the web page 802 maydisplay a first FAQ link 804, a second FAQ link 806, a third FAQ link808, a fourth FAQ link 810, a fifth FAQ link 812, and a sixth FAQ link814. Although the example illustrates six FAQ links, it is contemplatedthat any number of FAQ links may be displayed, or may include any otherinformation that the first instructions direct the web server 600 toprovide to the user device 104. The FAQ links 804-814 may include aquestion such as “How do you retrieve forgotten account information?”,“How do I create an account?”, and any other FAQ that the serviceprovider receives from users. Each FAQ link 804-814 may provide links toanswers and/or directions related to the FAQ.

The method 700 proceeds to decision block 710 where the web serverdetermines whether there is any user interaction with the customizedwebsite. In an embodiment, the web server 600 may determine whether theuser is interacting with the customized website. If the user is nolonger interacting or has closed out of the customized website, then themethod 700 may end and the web server 600 may provide the information tothe predictive management device 200. If the user interacts with thecustomized website, the method 700 may then proceed to block 712 wherethe web server transmits data associated with the interaction to thepredictive management device 200. In an embodiment, the web server 600may transmit any interactions by the user with the website hosted by theweb server 600 to the predictive management device 200. The interactionsmay be transmitted as second data that the predictive management device200 receives at block 312 of method 300 described above. The predictivemanagement device 200 may determine second instructions based on thesecond data according to method 300, and transmit the secondinstructions to the user interaction database 114 or the web server 600directly. The web server 600 may update the customized website based onthe second instructions and provide the updated customized website tothe user device 104 to be displayed on the display of the user device104.

Referring again to FIG. 8, the web server 600 may monitor the user'sinteractions with the customized web page 802 and if the user selects aFAQ link and then becomes inactive or leaves the website, the web server600 may report the result as second data to the predictive managementdevice 200 and the method 700 may end. If the web server 600 detectsother interactions such as the user logging into the user's account,then the web server 600 may provide this interaction and second dataassociated with the interaction to the predictive management server 200.The predictive management server may determine from the second data thata second condition is met and generate second instructions that are thenprovided directly to the web server 600 and/or to the user interactiondatabase 114 from which the web server 600 may access those secondinstructions. The second instructions may include a new set of FAQ linksto provide to the user that may be of particular interest to the userbased on data of the user's user account. The web server 600 may updatethe customized web page 802 to reflect the FAQ links provided by thesecond instructions.

FIG. 9 is a screen shot of an embodiment of a user device displaying anupdated customized web page 902 displayed via the web browser 800 of theuser device 104. Based on the information about the particular useraccount provided by the web server 600 to the predictive managementdevice 200, the predictive management device 200 may determine that aseventh FAQ illustrated by FAQ link 916 is the most relevant to theparticular user, and an eighth FAQ illustrated by FAQ link 918 isanother relevant FAQ, both of which may take the place of FAQ links 812and 814 of FIG. 8. For example FAQ link 812 may be a

FAQ link as to retrieve forgotten account information and FAQ link 814may be a FAQ link to establish a user account, and the predictivemanagement device 200 may determine that those are unlikely questions ofthe current user since the user is logged into their user account. Thepredictive management device 200 may determine that a likely FAQ for theparticular user, or a question that may result in a customer interactionwith a customer service representative, may be “Where is my refund?” ifthe user has requested a refund and not received the refund within anamount of time that typically causes the user to initiate acommunication session with a customer support representative about therefund. The predictive management device may generate the secondinstructions to cause the web server 600 to display the FAQ link relatedto customer refunds (e.g., the seventh FAQ link 916) at the top of theupdated customized web page 902. The second instructions may prioritizeother FAQ links based on the second data received. As illustrated in theupdated customized web page 902, the FAQ links are ordered as theseventh FAQ link 916, the second FAQ link 806, the fourth FAQ link 810,the third FAQ link 808, the eighth FAQ link 918, and the first FAQ link804 (e.g., in descending order of relevance.)

Referring now to FIG. 10, an embodiment of an interactive voice response(IVR) system 1000 is illustrated. In an embodiment, the IVR system 1000may be the IVR system 110 discussed above in FIG. 1. In the illustratedembodiment, the IVR system 1000 includes a chassis 1002 that houses thecomponents of the IVR system 1000, only some of which are illustrated inFIG. 10. For example, the chassis 1002 may house a processing system(not illustrated) and a non-transitory memory system (not illustrated)that includes instructions that, when executed by the processing system,cause the processing system to provide an IVR engine 1004 that isconfigured to perform the functions of the IVR engine 1004 and/or theIVR system 1000 discussed below. In a specific example, the IVR engine1004 may be software or instructions stored on a computer-readablemedium that is configured to gather frontend data about usersinteracting with the IVR system 1000 (e.g., voice response interactedwith, data inputted by the user, data regarding the user device 104,location of the user, identification information, acceptance rates ofinteractive responses, amount of time a user spends interacting with theIVR system, survey feedback from the user, if the interactive responsesresolved the user's issue, and other user related data that a IVR systemmay gather known in the art). In a specific example, the IVR engine 1004may be software or instructions stored on a computer-readable mediumthat is configured to generate and provide a customized voice responseto be presented at a user device (e.g., user device 104) based oninstructions generated by a predictive management device (e.g.,predictive management device 200) and provide any of the otherfunctionality that is discussed below.

The chassis 1002 may further house a communication engine 1006 that iscoupled to the IVR engine 1004 (e.g., via a coupling between thecommunication system 1006 and the processing system) and configured toprovide for communication through the network 122 and/or the network 106as detailed below. The communication engine 1006 may be software orinstructions stored on a computer-readable medium that allows the IVRsystem 1000 to send and receive information over the network 122 and/orthe network 106. The chassis 1002 may also house an IVR database 1008that is coupled to the IVR engine 1004 through the processing system.The IVR database 1008 may store interactive voice responses andinstruction used to generate customized interactive voice response basedon instructions generated and provided by the predictive managementdevice 200. While the IVR database 1008 has been illustrated as housedin the chassis 1002 of the IVR system 1000, one of skill in the art willrecognize that it may be connected to the IVR engine 1004 through thenetwork 122 and/or network 106 without departing from the scope of thepresent disclosure.

Referring now to FIG. 11, a method 1100 for generating a customized userexperience via an IVR system is illustrated. In the illustratedembodiment, one or more IVR systems may operate to perform or enable themethod 1100. IVR systems typically include a voice response; however itis contemplated that other interactive response systems such as aninteractive messaging response (IMR) system may fall under the scope ofthe disclosure with respect to method 1100. Method 1100 begins at block1102 where an IVR system receives a user interaction from a user device.In an embodiment, the IVR system 1000 may receive a communicationsession request such as a telephone call, a text message, an instantmessage, an email, or any other type of communication session requestknown in the art. The IVR system 1000 may be an initial system that isreached by a user trying to establish a communication session with acustomer service representative through the contact center system 112.The gateway 111 may receive a communication session request from theuser device 104. The gateway 111 may be a voice gateway, a sessionborder controller (SBC), or any media gateway that may route thecommunication session request to the IVR system 1000 for the user toperform self-service actions and/or to determine the appropriate queuesfor customer service representatives interacting with particular groupsof customer service terminals 124. The IVR system 1000 may gather anyinformation about the user interaction including user accountinformation, location information, user device type, time ofinteraction, any device identifier associated with the interaction(e.g., IP address, MAC address, telephone number, and any otheridentifier known in the art), and any other information that one ofskill in the art in possession of the present disclosure will recognizemay be captured from an initial user interaction with an IVR system. TheIVR system 1000 may obtain caller line identification (CLI) data fromthe network to help identify or authenticate the caller. Additionalcaller authentication data may include account number, personalinformation, password and biometrics (such as voice print). In anembodiment, the IVR system 1000 may transmit the information about theuser interaction to the predictive management device 200 as the firstdata described above with respect to method 300.

The method 1100 proceeds to block 1104 where the IVR system receivesinstructions from a predictive management device based on the userinteraction. In an embodiment, the IVR system 1000 directly receivesinstructions from the predictive management device 200 based on the userinteraction. Alternatively or additionally, the IVR system 1000 receivesinstructions from the user interaction database 114 based on the userinteraction. In an embodiment, the instructions may have been stored atthe IVR database 1008 before the user interaction with the user wasreceived. In an embodiment, the instructions may be global instructionsthat address general conditions on service provider system 102 that mayaffect a large group of users of the service provider system 102. Forexample, if there is a server failure on the service provider system 102that provides services to the users, the instructions may be configuredto address the server failure. In an embodiment, the instructions may bemidlevel instructions that address conditions for a particularpopulation of users. For example, there may be a condition in a specificcity or region such that users in that region more likely to initiate aninteraction with a customer service representative (e.g., the IVR system1000 may receive instructions based on the area code from which the userdevice is assigned.) Although the example illustrates location as acondition to provide the instructions at midlevel instructions, otherconditions may be relevant in determining instructions such as time ofday, events being provided by the service provider system 102 (e.g., acontent provider is providing a pay-per-view event), and otherconditions apparent to one skilled in the art.

In an embodiment, the instructions may be individual instructions thataddress a condition for a particular user, user account, and/or userdevice that is interacting with the IVR system 1000. In this particularexample, the IVR system 1000 may need to gather an identifier of theuser/user device such as user account information, telephone number,and/or a device identifier of the user device 104. For example, theindividual instructions may be based on recent activity of the user. TheIVR system 1000 may determine that a particular user is interacting withthe IVR system 1000 because of the telephone number associated with theuser device 104 of the user matches a telephone number associated with auser account. The IVR system 1000 may transmit the user accountinformation to the predictive management device 200. The predictivemanagement device 200 may determine instructions based on the conditionassociated with information of the user account. The user account mayinclude recent activity of the user associated with the user accountsuch that the recent activity may be provided as first data that may beused to determine an existing condition and generate instructions basedon the condition as in blocks 306 and 308 of method 300 described above.For example, the recent activity of a user account may indicate that theuser has interacted with the website of the web server 600 and accessedthe user's user account. The user account may indicate that the userpurchased two of the same items but different sizes and the items havebeen shipped and received by the user. The information associated withthe user's user account may also indicate that the user visited one ormore FAQ links of the web site that were associated with returns. Thepredictive management device 200 may determine that under theseconditions, the user is likely looking for return information for one ofthe items and may generate instructions that address returning itemsthat may or may not include information already accessed by the user atthe website. The predictive management device 200 may also determinethat the user may be looking for exchange information to exchange one ormore of the items for a different item. However, this option may be lesslikely than returning an item, which the instructions may take intoaccount. The instructions may also take into account other recentactivity performed on other customer service platforms by the user. Thisinformation may be used by the predictive management device 200 tocustomize the instructions for the IVR system 1000 to take into accountthe recent web site request and what information was provided to theuser while the user was interacting with the website hosted on webserver 600.

The method 1100 proceeds to block 1106 where the IVR system generates acustomized interactive response based on the instructions. In anembodiment, the IVR system 1000 may generate a customized interactiveresponse based on the instructions retrieved from the user interactiondatabase 114 and/or the predictive management engine 200. The IVR system1000 may be configured to provide prerecorded or dynamically generatedaudio with which the user may interact, and the IVR engine 1004 maygenerate the customized interactive response based on the instructionsand responses stored at the IVR database 1008. The method 1100 thenproceeds to block 1108 where the customized interactive response isprovided to the user device. In an embodiment, the IVR system 1000 mayprovide the customized interactive response to the user device 104. Theuser device 104 may convert the customized interactive response to audiothat is then provided to the user of the user device 104. In otherembodiments where the customized interactive response is text based, theIVR system 1000 may generate and provide the customized interactiveresponse to the user device 104, and the user device 104 may display thecustomized interactive response on a display of the user device 104.

The method 1100 proceeds to decision block 1110 where the IVR systemdetermines whether there is any user interaction with the customizedinteractive response. In an embodiment, the IVR system 1000 maydetermine whether the user is interacting with the customizedinteractive response. If the user is no longer interacting or has endedthe communication session, then the method 1100 may end and the IVRsystem 1000 may inform the predictive management device 200 that thecommunication session has ended. If the user interacts with thecustomized interactive response, then the method 1100 proceeds to block1112 where the IVR system 1000 transmits data associated with the userinteraction to the predictive management device 200. In an embodiment,the IVR system 1000 may transmit any user interaction with the IVRsystem 1000 to the predictive management device 200. The interactionsmay be transmitted as second data that the predictive management device200 receives at block 312 of method 300 described above. The predictivemanagement device 200 may determine second instructions based on thesecond data according to method 300 and transmit the second instructionsto the user interaction database 114 or the IVR system 1000 directly.The IVR system 1000 may update the customized interactive response basedon the second instructions, and provide an updated customizedinteractive response to the user device 104 for display on the displayof the user device 104 and/or to produce audio on the user device 104.

Referring now to FIG. 12, an embodiment of a contact center system 1200is illustrated. In an embodiment, the contact center system 1200 may bethe contact center system 112 discussed above in FIG. 1. In theillustrated embodiment, the contact center system 1200 includes achassis 1202 that houses the components of the contact center system1200, only some of which are illustrated in FIG. 12. For example, thechassis 1202 may house a processing system (not illustrated) and anon-transitory memory system (not illustrated) that includesinstructions that, when executed by the processing system, cause theprocessing system to provide an contact center engine 1204 that isconfigured to perform the functions of the contact center engine 1204and/or the contact center system 1200 discussed below. In a specificexample, the contact center engine 1204 may be software or instructionsstored on a computer-readable medium that is configured to gatherfrontend data about users interacting with the contact center system1200 and/or customer service representatives interaction with the usersvia the customer service terminal 124 of FIG. 1 (e.g., data inputted bythe user, data regarding the user device 104, location of the user,identification information, data inputs from a customer servicerepresentative via a customer service terminal 124, customer servicerepresentative specialties, customer service representative status,display rates of suggestions provided to customer servicerepresentatives, acceptance rates of suggestions, amount of time acustomer service representative spends on a user interaction, if thecustomer service representative opts out of a suggestion, if the userissue is resolved, and other user and/or customer service representativerelated data that contact center system may gather known in the art). Ina specific example, the contact center engine 1204 may be software orinstructions stored on a computer-readable medium that is configured togenerate and provide a customized customer service terminal GUI to bepresented at a customer service terminal (e.g., customer serviceterminal 124) based on instructions generated by a predictive managementdevice (e.g., predictive management device 200) and provide any of theother functionality that is discussed below that one of skill in the artin possession of the present disclosure will recognize as computerfunctionality that may be enabled by the customer service engine 1204 aswell.

The chassis 1202 may further house a communication engine 1206 that iscoupled to the contact center engine 1204 (e.g., via a coupling betweenthe communication system 1206 and the processing system) and configuredto provide for communication through the network 122, the network 106,and/or directly to the customer service terminal 124 or other serviceprovider system components as detailed below. The communication engine1206 may be software or instructions stored on a computer-readablemedium that allows the contact center system 1200 to send and receiveinformation over the network 122 and/or the network 106. In anembodiment, the communication engine 1206 may include other contactcenter system 1200 components such as an Automated Call Distributor(ACD), a Private Branch Exchange (PBX), and other contact center systemcomponents for directing telephone calls and data communications tocustomer service representatives. The ACD may be configured interactwith the IVR system 1000 for routing communication sessions from the IVRsystem 1000 to an appropriate customer service terminal 124 via the PBX.The ACD may be configured to interact with the gateway 111 of FIG. 1 indirecting communication sessions that do not first go to the IVR system1000, and directing communication sessions to the PBX. The ACD may beconfigured to interact with the web server 108 and customer accountdatabase 116 to provide any data communication sessions and/or customeraccount data that is associated with a user interacting with thecustomer service representative (e.g., via telephone) to a display ofthe customer service terminal 124.

The chassis 1202 may also house a contact center application database1208 that is coupled to the contact center engine 1204 through theprocessing system. The contact center application database 1208 maystore customer service applications for accessing and presenting userinformation from the user account database and instructions used togenerate customized customer service terminal graphical user interfaces(GUIs) based on instructions generated and provided by the predictivemanagement device 200. The contact center application database 1208 mayalso include a dashboard that houses the visual representations ofsuggestions that make up the customized customer service terminal GUIwith which the customer service representative may interact. While thecontact center 1208 has been illustrated as housed in the chassis 1202of the contact center system 1200, one of skill in the art willrecognize that it may be connected to the contact center engine 1204through the network 122 and/or network 106 without departing from thescope of the present disclosure.

Referring now to FIG. 13, a method 1300 for generating a customizedcustomer service graphical user interface (GUI) based on instructionsprovided by a predictive management device is illustrated. Method 1300begins at block 1302 where a contact center system establishes acommunication session between a user device and a customer serviceterminal. In an embodiment, the contact center system 1200 may receive atelephone call, a text message, an instant message, an email, video, orany other type of communication session known in the art from a userdevice 104. The communication session may be routed through the webserver 600 and/or the IVR system 1000 to the contact center system 1200.As previously described, the contact center system 1200 may include anACD that may queue and route telephone calls or other communicationsessions to appropriate customer service terminals 124 based on userselection, a user's telephone number, selected incoming line to thecontact center system 1200, time of day the call was processed, and anyother factors for routing calls in a contact center system 1200. The ACDmay also route data associated with the user of a voice communicationsession to the customer service terminal 124 to be displayed through acustomer service terminal GUI and/or data communication sessions fromthe user device 104 to the customer service terminal GUI. Thecommunication session may be a user initiated communication session witha customer service representative as described above, and may be acommunication session that the predictive management device 200 may beattempting to avoid according to a business goal of the serviceprovider.

In an embodiment, the web server 600 and/or the IVR system 1000 may havegathered information about the initial communication session beforereaching the contact center system 1200, including user accountinformation, location information, user device type, time ofinteraction, any device identifier associated with the interaction(e.g., IP address, MAC address, telephone number, and any otheridentifier known in the art), and any other information that one ofskill in the art in possession of the present disclosure would recognizemay be captured from an initial communication session before thecommunication session with the customer service terminal wasestablished. For example, the IVR system 1000 may obtain caller lineidentification (CLI) data from the network to help identify orauthenticate the caller. Additional caller authentication data mayinclude an account number, personal information, a password, andbiometrics (such as voice print). Similarly, the contact center system1200 may gather any information from a communication session requestoriginating from the user device 104 such as originating telephonenumber, device identifiers, service provider, any metadata associatedwith the requested communication session, and any data that may be usedto identifier the user of the user device 104 before the communicationsession is established with the customer service terminal 124. In anembodiment, the contact center system 1200 may transmit the informationabout the communication session request to the predictive managementdevice 200 as the first data described above with respect to method 300.

The method 1300 proceeds to block 1304 where the contact center systemreceives instructions from a predictive management device based on theinteraction. In an embodiment, the customer system 1200 directlyreceives instructions from the predictive management device 200.Alternatively or additionally, the contact center system 1200 receivesinstructions from the user interaction database 114. In an embodiment,the instructions may have been stored at the contact center applicationdatabase 1208 before the communication session request from the userdevice was received. In an embodiment, the instructions may be globalinstructions that address general conditions on service provider system102 that may affect a large group of users of the service providersystem 102. For example, if there is a server failure on the serviceprovider system 102 that provides services to the users, theinstructions may be configured to address the server failure. In anembodiment, the instructions may be midlevel instructions that addressconditions for a particular population of users. For example, there maybe a condition in a specific city or region such that users in thatregion are more likely to initiate an interaction with a customerservice representative, and the contact center system 1200 may receiveinstructions based on the area code from which the user device 104 isassigned. Although the example illustrates location as a condition toprovide the instructions at midlevel instructions, other conditions maybe relevant in determining instructions such as time of day, eventsbeing provided by the service provider system 102 (e.g., a contentprovider is providing a pay-per-view event), and other conditionsapparent to one skilled in the art.

In an embodiment, the instructions may be individual instructions thataddress a condition for a particular user, user account, and/or userdevice that is interacting with the contact center system 1200. In thisparticular example, the contact center system 1200 may need to gather anidentifier of the user/user device such as user account information,telephone number, and/or a device identifier of the user device 104 toprovide individual instructions. For example, the individualinstructions may be based on recent activity of the user. The contactcenter system 1200 may determine that a particular user is interactingwith the contact center system 1200 because of the telephone numberassociated with the communication session matches a telephone numberassociated with a user account. The contact center system 1200 maytransmit the user account information to the predictive managementdevice 200. The predictive management device 200 may determineinstructions based on a condition associated with the user account. Inan embodiment, the user account may include data relating to recentactivity of the user associated with the user account such that therecent activity may provide first data that is used to determine anexisting condition and to generate instructions based on the conditionas in blocks 306 and 308 of method 300 described above. For example, therecent activity of a user account that has interacted with the web siteof the web server 600 and accessed the user's account may indicate thatthe user purchased two of the same items with different sizes, and theitems have been shipped and received by the user. The predictivemanagement device 200 may determine that under these conditions the useris likely looking for return information for one of the items and maygenerate instructions that address returning items. The predictivemanagement device 200 may also determine that the user may be lookingfor exchange information to exchange one or more of the items for adifferent item. However, this scenario may be less likely than thereturning an item, which the instructions may take into account. Theinstructions may also take into account other recent activity performedon other contact center systems by the user. For example, the user mayhave recently accessed their user account on through the web server 600,or have just interacted with the IVR system 1000 prior to being routedto the contact center system 1200. This information gathered by the webserver 600 and/or IVR system 1000 may be used by the predictivemanagement device 200 to customize the instructions for the contactcenter system 1200 to take into account the recent website request andwhat information was provided to the user while the user was interactingwith the website hosted on web server 600 and/or the interactiveresponses interactions by the user with the IVR system 1000.

The method 1300 proceeds to block 1306 where the contact center systemgenerates a customized customer service terminal GUI based on theinstructions. In an embodiment, the contact center system 1200 maygenerate customized customer service terminal GUI based on theinstructions retrieved from the user interaction database 114 and/or thepredictive management engine 200. The contact center system 1200 isconfigured to generate customized customer service terminal GUI based onthe instructions and customer service application stored at the contactcenter application database 1208.

The method 1300 then proceeds to block 1308 where the customizedcustomer service terminal GUI is provided to the customer serviceterminal. In an embodiment, the contact center system 1200 may providethe customized customer service terminal GUI to the customer serviceterminal 124. The customer service terminal 124 may display the customerservice terminal GUI for the customer service representative of thecustomer service terminal 124. For example, the customer serviceterminal GUI may be displayed on a computer display of the customerservice terminal while the customer service representative is activelyparticipating in a communication session with the user of the userdevice 104 via the customer service terminal GUI and/or a telephone ofthe customer service terminal 124.

Referring to FIG. 14, a screen shot of an embodiment of a customerservice terminal displaying a customized customer service terminal GUI1400 is illustrated. In the particular example illustrated in FIG. 14,the customized customer service terminal GUI 1400 may include one ormore customer service applications. The customer service applicationsmay be provided via a web browser 1402 or other application graphicaluser interface known in the art. Each application may include one ormore sections (e.g., section 1404, section 1406, section 1408 andsection 1410) that may include one or more editable fields and/ornotification windows for instructions to be displayed or accessed. Forexample, the section 1404 may include a hierarchy of reasons and statusof the reasons for a particular user establishing the communicationsession with the customer service represented based on the instructionsprovided by the predictive management device 200. Section 1406 of thecustomer service terminal GUI 1400 may include user account informationof the user interacting with the customer service representative.Section 1408 may include recent history of user interactions with theservice provider and/or the customer service platforms. Section 1410 mayinclude customer notes of previous interactions with the user associatedwith the user account and may be configured to allow the customerservice representative to insert additional notes as the customerservice representative interacts with the user of the user device 104.Although simplified and specific examples of the customer serviceterminal GUI 1400 are illustrated, one skilled in the art will recognizethat many different configurations of the customer service terminal GUI1400 and information displayed and received through the customer serviceterminal GUI 1400 will fall under the scope of the present disclosure.

The method 1300 proceeds to decision block 1310 where the contact centersystem determines whether there is a customer service representativeinteraction with the customized customer service terminal GUI. In anembodiment, the contact center system 1200 may determine whether thecustomer service representative is interacting with the customizedcustomer service terminal GUI. If the customer service representative isno longer interacting with the customer service terminal GUI or hasended the communication session with the user, then the method 1300 mayend and the contact center system 1200 may provide the information tothe predictive management device 200 that the communication session hasended. If the customer service representative interacts with thecustomized customer service terminal GUI, then the method 1300 proceedsto block 1312 where the contact center system 1200 transmits dataassociated with the customer service representative to the predictivemanagement device 200. In an embodiment, the contact center system 1200may transmit any customer service representative interaction with thecontact center system 1200 to the predictive management device 200. Theinteractions may be transmitted as second data that the predictivemanagement device 200 receives at block 312 of method 300 describedabove. The predictive management device 200 may determine secondinstructions based on the second data according to method 300, and maytransmit the second instructions to the user interaction database 114 orthe contact center system 1200 directly. The contact center system 1200may then update the customized customer service terminal GUI based onthe second instructions, and provide the updated customized customerservice terminal GUI to the customer service terminal 124 to bedisplayed on the display of the customer service terminal 124 and/or toproduce audio on the customer service terminal 124.

Referring to FIG. 15, a screen shot of an embodiment of a customerservice terminal displaying an updated customized customer serviceterminal GUI 1500 is illustrated. In the particular example illustratedin FIG. 15, the updated customized customer service terminal GUI 1500may include one or more customer service applications that have beenupdated based on second instructions generated and provided by thepredictive management device 200. The customer service applications maybe provided via a web browser 1502 or other application graphical userinterface known in the art. The application may include one or moreupdated sections based on the customer service representativeinteractions provided by the customer service representative with thecustomer service terminal (e.g., updated section 1504, section 1506,section 1508 and section 1510). For example, updated section 1504 mayinclude an updated hierarchy of reasons, and a status for each reasonfor a particular user establishing the communication session with thecustomer service represented. For example, after a first reason ofsection 1404 was determined not to be the reason for a particular userestablishing the communication session, the predictive management devicemay have determined that a fifth reason is the most likely reason forthe communication session. Updated section 1506 of the customer serviceterminal GUI 1500 may include updated user account information of theuser interacting with the customer service representative. Updatedsection 1508 may include recent history of user interactions with theservice provider and/or the customer service platforms such as thecustomer service representative interaction that resulted in the updatedcustomer service terminal GUI 1500. Updated section 1510 may includeupdated customer notes including the previous interaction with the userthat caused the predictive management device 200 to update the customerservice terminal GUI 1500. Although simplified and specific examples ofthe updated customer service terminal GUI 1500 are illustrated, oneskilled in the art in possession of the present disclosure willrecognize that many different configurations of the updated customerservice terminal GUI 1500 and information displayed and received throughthe updated customer service terminal GUI 1500 will fall within thescope of the present disclosure.

Thus, a system and method for a cross-platform customer service systemhas been described that may predict possible user interactions with aservice provider system based on real-time and historical data that isprocessed by machine learning algorithms. Based on the predicted userinteractions, the cross-platform customer service system maypreemptively provide information to a user and/or perform actions togenerate and provide a customized user experience that may help achievea business goal of the service provider. The cross-platform customerservice system may provide instructions to multiple customer serviceplatforms based on data gathered from one of the customer serviceplatforms, as well as a backend monitoring system that gathers dataabout the service provider system so that any one of the customerservice platforms may have real-time information and instructions toprovide the customized user experience.

Referring now to FIG. 16, an embodiment of a network-based system 1600for implementing one or more processes described herein is illustrated.As shown, network-based system 1600 may comprise or implement aplurality of servers and/or software components that operate to performvarious methodologies in accordance with the described embodiments.Exemplary servers may include, for example, stand-alone andenterprise-class servers operating a server OS such as a MICROSOFT® OS,a UNIX® OS, a LINUX® OS, or other suitable server-based OS. It can beappreciated that the servers illustrated in FIG. 16 may be deployed inother ways and that the operations performed and/or the servicesprovided by such servers may be combined or separated for a givenimplementation and may be performed by a greater number or fewer numberof servers. One or more servers may be operated and/or maintained by thesame or different entities.

The embodiment of the networked system 1600 illustrated in FIG. 16includes a plurality of user devices 1602, a plurality customer serviceterminals 1604, a service provider system device 1606, and a pluralitythird party devices 1608 in communication over a network 610. Any of theuser devices 1602 may be the payer device 104, discussed above. Thecustomer service terminals 1604 may be the customer service terminals124 discussed above and may be operated by the customer servicerepresentatives discussed above. The service provider system device 1606may be the service provider system 102 including the devices discussedabove and may be operated by a payment service provider such as, forexample, PayPal Inc. of San Jose, Calif. The third party devices 1608may be the third party databases 126 discussed above and operated bydata brokers.

The user device 1602, the customer service terminal device 1604, theservice provider system device 1606, and the third party device 1608 mayeach include one or more processors, memories, and other appropriatecomponents for executing instructions such as program code and/or datastored on one or more computer readable mediums to implement the variousapplications, data, and steps described herein. For example, suchinstructions may be stored in one or more computer readable mediums suchas memories or data storage devices internal and/or external to variouscomponents of the system 1600, and/or accessible over the network 1610.

The network 1610 may be implemented as a single network or a combinationof multiple networks. For example, in various embodiments, the network1610 may include the Internet and/or one or more intranets, landlinenetworks, wireless networks, and/or other appropriate types of networks.

The user device 1602 may be implemented using any appropriatecombination of hardware and/or software configured for wired and/orwireless communication over network 1610. For example, in oneembodiment, the user device 1602 may be implemented as a personalcomputer of a user in communication with the Internet. In otherembodiments, the user device 1602 may be a smart phone, personal digitalassistant (PDA), laptop computer, and/or other types of computingdevices.

The user device 1602 may include one or more browser applications whichmay be used, for example, to provide a convenient interface to permitthe user to browse information available over the network 610. Forexample, in one embodiment, the browser application may be implementedas a web browser configured to view information available over theInternet.

The user device 1602 may also include one or more toolbar applicationswhich may be used, for example, to provide user-side processing forperforming desired tasks in response to operations selected by the user.In one embodiment, the toolbar application may display a user interfacein connection with the browser application.

The user device 1602 may further include other applications as may bedesired in particular embodiments to provide desired features to theuser device 1602. In particular, the other applications may include apayment application for payments assisted by a payment service providerthrough the service provider system device 1606. The other applicationsmay also include security applications for implementing user-sidesecurity features, programmatic user applications for interfacing withappropriate application programming interfaces (APIs) over the network1610, or other types of applications. Email and/or text applications mayalso be included, which allow the user to send and receive emails and/ortext messages through the network 1610. The user device 1602 includesone or more user and/or device identifiers which may be implemented, forexample, as operating system registry entries, cookies associated withthe browser application, identifiers associated with hardware of theuser device 1602, or other appropriate identifiers, such as a phonenumber. In one embodiment, the user identifier may be used by theservice provider system device 1606 and/or the customer service terminaldevice 1604 to associate the user with a particular account as furtherdescribed herein.

Referring now to FIG. 17, an embodiment of a user device 1700 isillustrated. The device 1700 may be any of the user devices discussedabove. The user device 1700 includes a chassis 1702 having a display1704 and an input device including the display 1704 and a plurality ofinput buttons 1706. One of skill in the art will recognize that the userdevice 1700 is a portable or mobile phone including a touch screen inputdevice and a plurality of input buttons that allow the functionalitydiscussed above with reference to the methods 300, 500, 700, 1100, and1300. However, a variety of other portable/mobile devices and/or desktopdevices may be used in the method 100 without departing from the scopeof the present disclosure.

Referring now to FIG. 18, an embodiment of a computer system 1800suitable for implementing, for example, the user devices, the customerservice terminals, the service provide system, and third partydatabases, is illustrated. It should be appreciated that other devicesutilized service provider system discussed above may be implemented asthe computer system 1800 in a manner as follows.

In accordance with various embodiments of the present disclosure,computer system 1800, such as a computer and/or a network server,includes a bus 1802 or other communication mechanism for communicatinginformation, which interconnects subsystems and components, such as aprocessing component 804 (e.g., processor, micro-controller, digitalsignal processor (DSP), etc.), a system memory component 1806 (e.g.,RAM), a static storage component 1808 (e.g., ROM), a disk drivecomponent 1810 (e.g., magnetic or optical), a network interfacecomponent 1812 (e.g., modem or Ethernet card), a display component 1814(e.g., CRT or LCD), an input component 1818 (e.g., keyboard, keypad, orvirtual keyboard), a cursor control component 1820 (e.g., mouse,pointer, or trackball), and/or a location determination component 1822(e.g., a Global Positioning System (GPS) device as illustrated, a celltower triangulation device, and/or a variety of other locationdetermination devices known in the art.) In one implementation, the diskdrive component 810 may comprise a database having one or more diskdrive components.

In accordance with embodiments of the present disclosure, the computersystem 1800 performs specific operations by the processor 1804 executingone or more sequences of instructions contained in the memory component1806, such as described herein with respect to the user devices, thecustomer service terminals, the service provide system, and/or the thirdparty databases. Such instructions may be read into the system memorycomponent 1806 from another computer readable medium, such as the staticstorage component 1808 or the disk drive component 1810. In otherembodiments, hard-wired circuitry may be used in place of or incombination with software instructions to implement the presentdisclosure.

Logic may be encoded in a computer readable medium, which may refer toany medium that participates in providing instructions to the processor1804 for execution. Such a medium may take many forms, including but notlimited to, non-volatile media, volatile media, and transmission media.In one embodiment, the computer readable medium is non-transitory. Invarious implementations, non-volatile media includes optical or magneticdisks, such as the disk drive component 1810, volatile media includesdynamic memory, such as the system memory component 1806, andtransmission media includes coaxial cables, copper wire, and fiberoptics, including wires that comprise the bus 1802. In one example,transmission media may take the form of acoustic or light waves, such asthose generated during radio wave and infrared data communications.

Some common forms of computer readable media includes, for example,floppy disk, flexible disk, hard disk, magnetic tape, any other magneticmedium, CD-ROM, any other optical medium, punch cards, paper tape, anyother physical medium with patterns of holes, RAM, PROM, EPROM,FLASH-EPROM, any other memory chip or cartridge, carrier wave, or anyother medium from which a computer is adapted to read. In oneembodiment, the computer readable media is non-transitory.

In various embodiments of the present disclosure, execution ofinstruction sequences to practice the present disclosure may beperformed by the computer system 1800. In various other embodiments ofthe present disclosure, a plurality of the computer systems 800 coupledby a communication link 1824 to the network 610 (e.g., such as a LAN,WLAN, PTSN, and/or various other wired or wireless networks, includingtelecommunications, mobile, and cellular phone networks) may performinstruction sequences to practice the present disclosure in coordinationwith one another.

The computer system 1800 may transmit and receive messages, data,information and instructions, including one or more programs (i.e.,application code) through the communication link 1824 and the networkinterface component 1812. The network interface component 1812 mayinclude an antenna, either separate or integrated, to enabletransmission and reception via the communication link 1824. Receivedprogram code may be executed by processor 1804 as received and/or storedin disk drive component 1810 or some other non-volatile storagecomponent for execution.

Where applicable, various embodiments provided by the present disclosuremay be implemented using hardware, software, or combinations of hardwareand software. Also, where applicable, the various hardware componentsand/or software components set forth herein may be combined intocomposite components comprising software, hardware, and/or both withoutdeparting from the scope of the present disclosure. Where applicable,the various hardware components and/or software components set forthherein may be separated into sub-components comprising software,hardware, or both without departing from the scope of the presentdisclosure. In addition, where applicable, it is contemplated thatsoftware components may be implemented as hardware components andvice-versa.

Software, in accordance with the present disclosure, such as programcode and/or data, may be stored on one or more computer readablemediums. It is also contemplated that software identified herein may beimplemented using one or more general purpose or specific purposecomputers and/or computer systems, networked and/or otherwise. Whereapplicable, the ordering of various steps described herein may bechanged, combined into composite steps, and/or separated into sub-stepsto provide features described herein.

The foregoing disclosure is not intended to limit the present disclosureto the precise forms or particular fields of use disclosed. As such, itis contemplated that various alternate embodiments and/or modificationsto the present disclosure, whether explicitly described or impliedherein, are possible in light of the disclosure. For example, the aboveembodiments have focused on payees and payers; however, a payer orconsumer can pay, or otherwise interact with any type of recipient,including charities and individuals. The payment does not have toinvolve a purchase, but may be a loan, a charitable contribution, agift, etc. Thus, payee as used herein can also include charities,individuals, and any other entity or person receiving a payment from apayer. Having thus described embodiments of the present disclosure,persons of ordinary skill in the art will recognize that changes may bemade in form and detail without departing from the scope of the presentdisclosure. Thus, the present disclosure is limited only by the claims.

What is claimed is:
 1. A system, comprising: a non-transitory memory;one or more hardware processors coupled to the non-transitory memory andconfigured to read instructions from the non-transitory memory to causethe system to perform operations comprising: receiving a first userinteraction from a user device; retrieving first instruction from apredictive management device based on the first user interaction;generating a first customized user experience based on the firstinstructions; and providing the first customized user experience to theuser device.
 2. The system of claim 1, wherein the operations furthercomprises providing first user interaction data to the predictivemanagement device, wherein the predictive management device determinesthe first instructions based on the first user interaction data.
 3. Thesystem of claim 1, wherein the operations further comprise: receiving asecond user interaction from the user device with the customized userexperience; and providing second user interaction data to the predictivemanagement device, wherein the predictive management device determinessecond instructions based on the second user interaction data.
 4. Thesystem of claim 3, wherein the operation further comprise: retrievingthe second instruction from a predictive management device; generating asecond customized user experience based on the second instructions; andproviding the second customized user experience to the user device. 5.The system of claim 1, wherein the first customized user experience is apersonalized website to be displayed at the user device.
 6. The systemof claim 1, wherein the first customized user experience is a customizedinteractive response provided to the user device from an interactivevoice response (IVR) system.
 7. The system of claim 1, wherein the firstcustomized user experience is a customized customer service terminalgraphical user interface provided to a customer service terminal from acontact center system.
 8. A method for predictive cross-platformcustomer service, comprising: receiving, by a customer service platform,a first user interaction from a user device; retrieving, by the customerservice platform, first instruction from a predictive management devicebased on the first user interaction; generating, by the customer serviceplatform, a first customized user experience based on the firstinstructions; and providing, by the customer service platform, the firstcustomized user experience to the user device.
 9. The method of claim 8,further comprising providing, by the customer service platform, firstuser interaction data to the predictive management device, wherein thepredictive management device determines the first instructions based onthe first user interaction data.
 10. The method of claim 8, furthercomprising: receiving, by the customer service platform, a second userinteraction from the user device with the customized user experience;and providing, by the customer service platform, second user interactiondata to the predictive management device, wherein the predictivemanagement device determines second instructions based on the seconduser interaction data.
 11. The method of claim 10, further comprising:retrieving, by the customer service platform, the second instructionfrom a predictive management device; generating, by the customer serviceplatform, a second customized user experience based on the secondinstructions; and providing, by the customer service platform, thesecond customized user experience to the user device.
 12. The method ofclaim 8, wherein the customer service platform is a web server and thefirst customized user experience is a personalized website to bedisplayed at the user device.
 13. The method of claim 8, wherein thecustomer service platform is an interactive voice response (IVR) systemand the first customized user experience is a customized interactiveresponse provided to the user device from the IVR system.
 14. The methodof claim 8, wherein the customer service platform is a contact centersystem and the first customized user experience is a customized customerservice terminal graphical user interface provided to a customer serviceterminal from the contact center system.
 15. A non-transitorymachine-readable medium having stored thereon machine-readableinstructions executable to cause a machine to perform operationscomprising: receiving a first user interaction from a user device;retrieving first instruction from a predictive management device basedon the first user interaction; generating a first customized userexperience based on the first instructions; and providing the firstcustomized user experience to the user device.
 16. The non-transitorymachine-readable medium of claim 15, wherein the operations furthercomprise: providing first user interaction data to the predictivemanagement device, wherein the predictive management device determinesthe first instructions based on the first user interaction data.
 17. Thenon-transitory machine-readable medium of claim 15, wherein theoperations further comprise: receiving a second user interaction fromthe user device with the customized user experience; and providingsecond user interaction data to the predictive management device,wherein the predictive management device determines second instructionsbased on the second user interaction data.
 18. The non-transitorymachine-readable medium of claim 15, wherein the operations furthercomprise: retrieving the second instruction from a predictive managementdevice; generating a second customized user experience based on thesecond instructions; and providing the second customized user experienceto the user device.
 19. The non-transitory machine-readable medium ofclaim 15, wherein the first customized user experience is a personalizedwebsite to be displayed at the user device.
 20. The non-transitorymachine-readable medium of claim 15, wherein the first customized userexperience is a customized customer service terminal graphical userinterface provided to a customer service terminal from a contact centersystem.